Turbulence and winds aloft detection system and method

ABSTRACT

A turbulence and winds aloft detection system may include an image capturing device for capturing a plurality of images of a visual feature of a selected celestial object; and an image processor configured to compare the plurality of images of the visual feature to detect a transit of a turbule of turbulent air between the image capturing device and the selected celestial object; compensate for one or more of apparent visual motion of celestial objects due to a planet&#39;s translation and rotation, the moon&#39;s revolution about the planet, and the atmosphere&#39;s refractive displacement of celestial objects; and compute a measurement of at least one of a velocity of the turbule and a height of the turbule relative to the planet.

FIELD

Embodiments of the subject matter described herein relate generally to asystem and method for estimating turbulence and winds aloft in theatmosphere, and in particular to using a camera-based system to developturbulence and wind profiles of the atmosphere using features ofcelestial bodies.

BACKGROUND

Measuring atmospheric conditions including turbulence and winds aloftallows aircraft and airborne vehicles to make flight adjustments toachieve a desired level of performance and avoid undesirable flyingconditions. Winds aloft affect the fuel consumption and speed ofaircraft. Airplane encounters with clear air turbulence at cruisealtitude may produce serious injury. Clear air turbulence is difficultto forecast and even more difficult to detect with current methods.Clear air turbulence is turbulence that results where there are noclouds, precipitation, or visible particles such as dust in the air.

In addition, measuring the present state of atmospheric conditions isnecessary to forecast future atmospheric events such as storms.Measuring atmospheric conditions can be performed to varying degreesusing ground-based instrumentation, by sensors carried aloft in balloonsor other airborne vehicles, by sensors in aircraft as they pass througha region of atmosphere, and by using predictive modeling based on pastmeasurements.

However, over oceans and in underdeveloped regions of the world,ground-based instrumentation and dedicated sensor equipment like weatherballoons either do not exist or it may be economically impractical tocover an area with sufficient sensors to provide the desired level ofaccuracy. Additionally, aircraft may pass through an area tooinfrequently to provide current conditions for other later aircraft.Dynamic atmospheric conditions generally make modeling grow less preciseover time, and although good for approximating general conditions forregional conditions, modeling can be inaccurate at finer granularities.Sensors, and especially fixed instrumentation, are limited to surveyingportions of the atmosphere proximate to the sensor apparatus at the timethe sensor measurements were made. A moving aircraft or airborne vehiclemay travel through multiple overlapping zones of coverage and areaswithout coverage during a flight.

SUMMARY

In one embodiment, a turbulence and winds aloft detection system mayinclude an image capturing device for capturing a plurality of images ofa visual feature of a selected celestial object; and an image processorconfigured to compare the plurality of images of the visual feature todetect a transit of a turbule of turbulent air between the imagecapturing device and the selected celestial object; compensate for oneor more of apparent visual motion of celestial objects due to a planet'stranslation and rotation, the moon's revolution about the planet, andthe atmosphere's refractive displacement of celestial objects; andcompute a measurement of at least one of a velocity of the turbule and aheight of the turbule relative to the planet.

In another embodiment, a turbulence and winds aloft detection system mayinclude an image capturing device for capturing a plurality of images ofa visual feature of a selected celestial object; a device for sensingmotion of the image capturing device relative to the Earth; and an imageprocessor configured to compare the plurality of images of the visualfeature to detect a transit of a turbule of turbulent air between theimage capturing device and the selected celestial object, receive asignal from the motion sensing device to continuously estimate avelocity of the image capturing device relative to the Earth, andcompute a measurement of at least one of a velocity of the turbulerelative to the Earth and a height of the turbule relative to the Earth.

In yet another embodiment, a method of detecting turbulence and windsaloft may include capturing a plurality of images of a visual feature ofa selected celestial object; comparing the plurality of images to detectthe transit of a turbule of turbulent air in front of the selectedcelestial object; and processing the plurality of images to compensatefor one or more of apparent visual motion of celestial objects due to aplanet's translation and rotation, the moon's revolution about theplanet, and the atmosphere's refractive displacement of celestialobjects; and computing a measurement of at least one of an angularvelocity of the turbule and the height of the turbule.

In still another embodiment, a method of detecting turbulence and windsaloft may include capturing a plurality of images of a visual feature ofa selected celestial object with an image capturing device; sensingmotion of the image capturing device relative to the Earth; processingthe plurality of images of the visual feature to detect a transit of aturbule of turbulent air between the image capturing device and theselected celestial object; using sensed motion of the image capturingdevice to continuously estimate a velocity of the image capturing devicerelative to the Earth; and computing a measurement of at least one of avelocity of the turbule relative to the Earth and a height of theturbule relative to the Earth.

The features, functions, and advantages discussed can be achievedindependently in various embodiments of the present invention or may becombined in yet other embodiments further details of which can be seenwith reference to the following description and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying figures depict various embodiments of the system andmethod for measuring the turbulence and winds aloft in the atmosphereusing solar and lunar observable features. A brief description of eachfigure is provided below. Elements with the same reference number ineach figure indicate identical or functionally similar elements.Additionally, the left-most digit(s) of a reference number indicate thedrawing in which the reference number first appears.

FIG. 1A is a diagram of a turbulence detection system on a shiptraversing the earth, an aircraft in flight above the earth, and therelationship of the ship and the aircraft in relation to winds aloft andcelestial objects;

FIG. 1B is a diagram of a granule of the sun being focused onto a chargecoupled device through a lens and the effect of a turbule on theposition of the granule in the image;

FIG. 2A is a picture of the sun seen through a helium I filter;

FIG. 2B is a picture of the sun seen through a hydrogen alpha filter;

FIG. 2C is a picture of the moon seen through a polarizing filter;

FIG. 3A is a diagram illustrating the geometry of camera systemvisualizing a turbule of turbulent air as it passes in front of the sun;

FIG. 3B is an exaggerated view of the effect that a turbule of turbulentair has on the edge of the sun's disc as visualized by the camerasystem;

FIG. 3C is an exaggerated view of the effect that a turbule of turbulentair has on the edge of the sun's disc as visualized by the camerasystem;

FIG. 4A is a diagram of a two camera system for visualizing turbules anddetermining the distance to the turbules;

FIG. 4B is a diagram illustrating the differences in turbule position asimaged by two cameras displaced by distance d;

FIG. 5A is a alternative diagram of the geometry of a two camera systemfor visualizing turbules and determining the distance to the turbules;

FIG. 5B is an alternative diagram illustrating a method of visuallydetermining the angular offset between two cameras that are visualizingthe same turbule from separated viewing positions;

FIG. 6A is a diagram illustrating two different altitudes and pathstaken by two different turbules;

FIG. 6B is a graph showing the paths of the two turbules that are atdifferent altitudes;

FIG. 7A are images captured by a camera of a first turbule at fourdifferent time intervals as it transits in front of the sun;

FIG. 7B are images captured by a camera of a second turbule at fourdifferent time intervals as it transits in front of the sun;

FIG. 7C are images captured by a camera showing the relative paths of afirst turbule and a second turbule at four different times intervals asthey transit in front of the sun;

FIGS. 8A, 8B, and 8C are images of the differences between twoconsecutive images of the two turbules of FIG. 7C;

FIGS. 9A and 9B are contour plots showing the correlation of the angularvelocities of the two turbules computed from the difference images ofFIGS. 8A, 8B, and 8C;

FIGS. 10A and 10B are images of left and right camera sequencesrespectively of a turbule transiting in front of the sun where theturbule is imaged by both the left and right cameras during a commoninterval of time;

FIG. 11 is an illustration of the use of angular offset to correlate theimages of the turbule when the turbule is imaged by both cameras duringa common interval of time;

FIGS. 12A and 12B are images of left and right camera sequencesrespectively of a turbule transiting in front of the sun where theturbule is not visible to both cameras during a common interval of time;

FIG. 13 is an illustration of a multi-dimensional solution to correlatethe images of the turbule when the turbule is imaged by differentcameras at different times; and

FIG. 14 is a diagram showing relationships between velocity vectors of acamera used in an embodiment and a turbule.

DETAILED DESCRIPTION

The following detailed description is merely illustrative in nature andis not intended to limit the embodiments of the invention or theapplication and uses of such embodiments. Furthermore, there is nointention to be bound by any expressed or implied theory presented inthe preceding technical field, background, brief summary or thefollowing detailed description.

Clear air turbulence is difficult to forecast and even more difficult todetect using current methods. Clear air turbulence is turbulence thatresults where there are no clouds, precipitation, or visible particlessuch as dust in the air. Pilots may learn of clear air turbulence fromforecasts and other pilots that have recently flown through a pocket ofturbulence. Generally, pilots turn on a “seat belt required” lightand/or slow their aircraft's speed in anticipation of passing throughsuspected pockets of turbulence to reduce structural stresses on theaircraft and reduce discomfort to passengers. However, if the pilot isunaware of turbulence, the pilot may have little warning time to alertthe passengers or otherwise change the configuration and velocity of theaircraft.

A turbulence and winds aloft measurement system 100 detects turbulencein the atmosphere and communicates it to pilots, which enables thepilots to maneuver their aircraft to avoid any turbulent pockets of air.In one embodiment, the turbulence and winds aloft measurement system 100warns the pilot of turbulence in the path of the aircraft. In anotherembodiment, turbulence and winds aloft measurement system 100 provides avisual navigational aid to enable a pilot to navigate around pockets ofturbulent air. The turbulence and winds aloft measurement system 100 mayimprove air safety, allowing airplanes to fly at cruise speeds with areduced risk of running into unexpected turbulence that could damage theairplane or harm passengers. The turbulence and winds aloft measurementsystem 100 also may increase the comfort of passengers in the airplaneby allowing the pilot to navigate around pockets of turbulence or, ifthe turbulence is widespread, by allowing the pilot to change theairplane's speed profile or configuration and navigate through the leastturbulent areas of the sky. Further, reducing the amount of turbulencethat an airplane flies through over the airplane's useful life may alsoreduce the stresses on airframe and engine components that accrue duringa lifetime of continuous operation. The turbulence and winds aloftmeasurement system 100 therefore reduces component fatigue, permitssafer long term operation of the aircraft, and reduces or shortensnecessary maintenance cycles.

The turbulence and winds aloft measurement system 100 allows pilots usethe winds aloft estimates to maneuver their aircraft to minimize theeffect of headwinds and maximize tailwinds. Because winds aloft have astrong effect on airliner fuel consumption, measurements or predictionsof winds aloft can be used to increase aircraft efficiency and maximizeoperating range.

System Components and Operation

As shown in FIG. 1A, a turbulence and winds aloft measurement system,generally designated 100, may obtain optical turbulence information ofthe atmosphere using observable features of the sun 124 and moon 122 orother celestial objects 128, for example a grouping of stars 126, suchas a constellation or asterism, to predict atmospheric conditions in theparcel of atmosphere. The turbulence and winds aloft measurement system100 may use distortions in visual measurements of observable features ofthe sun 124, moon 122, stars 126, or other celestial objects 128, suchas planets and the position of moons around the planets, to measure andtrack refractivity fluctuations in intervening parcels of atmosphere.The refractivity fluctuations correspond to turbules 112 of turbulentair, and tracking the turbules 112 allows the turbulence and winds aloftmeasurement system 100 to determine the velocity of winds aloft 114. Inaddition to tracking turbules 112 or turbulence in general, the visualmeasurements can be used to improve atmospheric models, for examplemodels of winds aloft 114, and thereby improve weather forecasts and/oraircraft routing.

In an embodiment, the turbulence and winds aloft measurement system 100may include a mobile platform or vehicle 102, for example a ship,traversing a section of the earth 110, a first camera 104 a, and asecond camera 104 b, a position and orientation system 106, and acomputer 108. In embodiments, the mobile platform 102 may be a marinevessel, a land vehicle, a building or structure, an aircraft, aspacecraft, or any other stationary or mobile platform positioned with aview of the surrounding atmosphere.

The cameras 104 a, 104 b (collectively 104) may be mounted on or to thevehicle 102 and separated by a modest distance. In an embodiment, thecameras 104 may be mounted on different sides of the vehicle 102. Acomputer 108 may analyze images from the cameras 104. The computer 108may be any suitable computing platform capable of manipulating digitalimage data, including but not limited to a PC, workstation, a customizedcircuit board, or an image processor. The cameras 104 may becommunicatively linked to the computer 108 that receives the images fromthe cameras 104, either by hard wiring or wireless communicationsnetwork, or may be a unitary device. In an embodiment, the computer 108is physically located on the vehicle 102. In embodiments, the computer108 may be physically located on another platform or operations center,for example at a weather service provider 130. In embodiments, data fromcameras 104 may be networked to one or more computers via a network orplurality of networks.

In an embodiment, the cameras 104 may use a telephoto lens. Inoperation, the cameras 104 may be pointed at a celestial object 128 or aparticular feature of a celestial object 128 having sufficient knowndetail, and a series of images or video may be delivered to the computer108. In embodiments, the celestial object 128 may be the moon 122, thesun 124, a grouping of stars 126, planets, or planet and moonscombination. For example, the stars 126 may be a well-knownconstellation of stars 126 such as the Pleiades, an asterism such as theLittle Dipper, or any other grouping of stars having close proximity toone another. The particular feature of a celestial object may be an edgeof a solar disc, a sunspot, a solar granule, an edge of a lunar disc, alunar crater, a lunar mountain range, a lunar shadow, a relativeposition of each of the plurality of stars, and a position of moonsabout the planet. The cameras 104 may output digitized data of the imageto the computer 108. In another embodiment, the computer 108 maydigitize analog inputs from the cameras 104 into digital images using adigital frame grabber.

The images from the cameras 104 may be analyzed to detect small localdeviations in the refractive index of air. For example, light returningto the cameras 104 from the sun 124 passes through the atmosphere alonglight path 132. Changes in refraction are due to the density andcomposition of air in the atmosphere, for example due to differences inhumidity levels, temperatures, and pressures. As a result of the smalllocal changes in refraction due to turbulence, features of the sun 124can appear shifted spatially. The mean-square angular displacement ofsmall features may be given by a well-known formula shown in Equation(1). In this formula, φ is the angular displacement in radians, anglebrackets < > indicate the mean expected value of the enclosed quantity,D is the camera aperture, L is the total distance from the light sourceto the camera, η is a measure of distance along the optical path fromthe light source to the camera, and C_(n) ² is a measure of opticalturbulence at each point along the path. C_(n) ² is mathematicallyrelated to mechanical turbulence, which can pose a danger to aircraft.<φ²>=2.91D ^(−1/3)∫₀ ^(L) C _(n) ²(η)dη  Equation (1)

Referring now to FIG. 1B, a telephoto lens 142 focuses light from thesun 124 through a helium I filter 200 onto a charge coupled device (CCD)140. For purposes of illustration only, part of a granule 202 of the sun124 may be shown on the CCD 140 as an inverted image 146. The invertedimage 146 is where the granule 202 is resolved on the CCD 140 due thedistortion caused by the turbule 112 carried in the winds aloft 114. Thedashed inverted image 144 illustrates where the solar granule 202 willbe imaged once the turbule 112 passes. Turbulence-induced deviations inthe refractive bending of light can be on the order of threemicroradians or less, which may be too small to be detected accuratelyby many cameras 104 using normal snapshot lenses. To increase accuracyand provide a finer level of granularity, the cameras 104 in theturbulence and winds aloft measurement system 100 use a telephotofocusing system such as a lens or mirror having a long focal length thatmagnifies the image and provides a suitable resolution for imaging bythe cameras 104.

In an embodiment, the telephoto lens 142 and the pixel resolution of theimage capturing element, for example a CCD 140 or charge coupled device,are adapted to resolve at least 2.5 microradians of angle. For example,a telephoto lens having a 30-cm aperture and a 1-meter focal length canresolve approximately 2.5×10⁻⁶ radians in visible wavelengths whencoupled with a 1×1 cm CCD chip having 2.5 micron pixels arranged in a4000×4000 pixel matrix. In one embodiment, the telephoto lens 142 is azoom lens, capable of adjusting the magnification and therefore allowingthe system operator to selectively trade off measurement accuracy for awider field of view.

In an embodiment, the cameras 104 include a CCD 140 having a very finepitch, or a similar image capturing means, which is used to gather animage, either alone or in combination with a telephoto lens. To maximizethe resolution, the CCD 140 may be a black and white CCD. Color CCDsgenerally use tiny filters arranged in a pattern over the CCD elements,which can cause unwanted image artifacts such as color changes nearsharp edges of object depending upon how the light falls onto the CCDchip. Edge artifacts are unwanted image distortions that have thepotential of being misinterpreted by the computer. In other embodiments,the system uses a 3-CCD camera 104 that divides the image into threedifferent CCDs, for example using birefringent materials, and thereforedoes not induce unwanted edge artifacts.

In embodiments, the cameras 104 may be digital frame cameras, videocameras, high-resolution CCD cameras, or HD camcorders. In embodiments,to enhance the image depth and dynamic range of the captured image, thecameras 104 selectively use filters, such as a solar filter, a hydrogenalpha filter, a helium I filter, a polarization filter, a neutraldensity filter, or a red filter to avoid backscattered blue light. Inembodiments, the optical filters reduce the brightness and/or pass onlyselected wavelengths of light. In embodiments, the cameras 104additionally may be infrared cameras or selectively use imageintensifiers, such as a night vision tubes, to allow the turbulence andwinds aloft measurement system 100 to perform better in low lightsituations such as when viewing unlit portions of the moon 122 or othercelestial objects 128 at night time. In embodiments, the cameras 104 maybe image capturing devices using a CCD chip, an analog sensor, a linearsensor such as a linear sensor array, or any other photosensitive sensorcapable of determining fine pitch in a visual scene.

In an embodiment, the cameras 104 are mounted on a rotatable swivelmounts that allow the cameras 104 to be rotated to view differentportions of the sky. In an embodiment, the cameras 104 are mounted onmulti-axis gimbals, allowing the cameras 104 to be angularly rotated inany direction. In these embodiments, the cameras 104 may be rotated ororiented in order to scan a larger area. The outputs from the cameras104 may be synchronized with an output from a rotational encoder orother similar orientation identifying means to correlate images from thecameras 104 with the orientation of the cameras 104.

The motion of the cameras 104 may be linked to the motion of the vehicle102, for example through a position and orientation system 106, such asa navigation and control system, a global positioning satellite (GPS)receiver, an inertial measurement unit (IMU), or any similar system orcombination of systems. The IMU measures changes in camera 104orientation due to rotation or twisting of the vehicle 102 and may beused to maintain orientation of the cameras 104 toward a desiredcelestial object 128. In an embodiment, one or both of the cameras 104may be substantially fixed and a rotatable mirror is used to change thedirection of viewing of or more of the cameras 104. In an embodiment,the mirrors may be first surface mirrors for better clarity. In anembodiment, the cameras 104 may be mounted in vibration reducing mounts.In an embodiment, the cameras 104 may be gyroscopically stabilized.

Image Processing

Continuing to refer to FIG. 1A, the computer 108 processes one or moreimages from the cameras 104. The processing identifies visual featureswhose physical location is well known, e.g., features on the sun 124 ormoon 122. The sun 124 and the moon 122 both have visible features thatcan be distorted by turbulence in ways that allow detection of theturbulence.

Referring now to FIG. 2C, the lunar features 206 of the moon 122,including mountains and craters, are well known and are static. However,different portions of the moon 122 are illuminated by the sun 124,depending upon the particular lunar phase. The angle of illumination oflunar features 206 by the sun 124 also varies with the particular lunarphase, creating shadows that vary with the particular lunar phase.Polarizing filters and neutral density filters can be used to enhancethe resolving capability of the cameras 104. The moon 122 is shown inFIG. 2C using a polarizing filter 220. The moon 122 also wobblesslightly, thus allowing slightly more than half of the surface of themoon 122 to be usable as visual features.

Referring to FIGS. 2A and 2B, to detect features of the sun 124, specialfilters such as solar filters, hydrogen alpha filters, helium I filters,etc. are utilized. Using solar filters, features such as the edge of thesun 124 and sunspots 204, when present, can be resolved by the cameras104. Using filters such as helium I filters 200 and hydrogen alphafilters 210, the sun 124 also presents full-time surface features duringdaylight hours called “granules” 202. FIGS. 2A and 2B show granules 202.Granules 202 are always present, are easily observable with a telephotolens and a narrowband spectral filter and have a fine-grained texture.The sun 124 is shown in FIG. 2A using a helium I filter 200. The sun 124is shown in FIG. 2B using a hydrogen alpha filter 210. Granules 202provide a good background against which to detect turbules 112.

Referring again to FIG. 1A, using the spatial position (in pixel rowsand columns) of each visual feature on the focal plane, the pitch ofpixels in the camera focal plane, and the focal length of the lens, thecomputer 108 measures the angular position of those visual features inthe scene. The computer 108 may compare the visual features in aplurality of frames to detect changes in the angular position of thosefeatures. The changes in angular position may be caused by differencesin the refractivity of the atmosphere due to turbulence, or turbules112, and winds aloft 114. For ease of exposition, the following examplesuse the sun 124 as the background object for detecting turbules 112 andwinds aloft 114, however any celestial object 128 including the moon122, the sun 124, stars 126 and planets may be utilized with appropriatelenses and filters.

The computer 108 processes a series of time-tagged frames from eachcamera 104. When no clouds or turbulence is present in the field ofview, each frame will look essentially the same as the next frame fromthe same camera 104. For example, two consecutive frames of the sun 124will look essentially the same, with a slight change in position of thesun 124 due to the ordinary movement of the sun 124 relative to theearth 110. When turbulence is present, however, some parts of the sun124 will appear distorted, and the distortion will vary from frame toframe. A feature in one frame captured at time t₀ cannot be easilyregistered with that feature in a later frame at time t₀+Δt.

Registering features in one frame with the same features in anotherframe involves using linear image transformation methods. In acomparison between a two frames, for example a frame at time t₀ and aframe at time t₀+Δt, features in one frame can be easily registered withsimilar features in another frame using simple geometrictransformations. In one embodiment, the computer 108 performs atransformation of a first frame at time t₀ into a predicted subsequentframe, and compares the predicted subsequent frame with the actualsubsequent frame at time t₀+Δt. In another embodiment, the computer 108performs a similar process but transforms the subsequent frame into apredicted first frame. However, transforming the subsequent frame hasthe disadvantage that the system must wait until the subsequent frame isreceived by the computer 108 before performing the transformation,creating a possible time lag.

In another embodiment, both a first and a subsequent frame may betransformed to an internal standard frame format used by the computerbefore being compared. This embodiment has the advantage in that eachframe may be transformed independently of any camera-related artifactsof the other frame and simplifying computations. For example, using aninternal standard frame, each frame can be different in terms of angle,rotation, zooming, and aperture and then mapped to the angle, rotation,zoom level and aperture of the internal standard frame. Further, usingthe internal standard frame simplifies comparing frames from differentcameras 104, which may have different focal lengths or may look at thesame scene from different angles, for example if two cameras 104 aremounted on opposite sides of a ship, or vehicle 102.

To perform the transformation, the computer 108 performs an estimate ofthe motion of the vehicle 102 including changes in direction andorientation, for example by using information from an onboard inertialnavigation system and/or a GPS system. The computer 108 also may performan estimate of the motion of the feature, for example the small changesin position of the sun 124 or moon 122 relative to the earth 110. Thecomputer 108 uses the motion estimates along with the time between theframes, t₀ and t₀+Δt to perform a transformation of features in one orboth frames. The computer 108 registers the frames by adjusting thesize, position, and orientation of the feature in one or both of theframes, for example by registering the features in frame at t₀ to thefeature in the frame at t₀+Δt. In this example, the frame at t₀ isdigitally translated, scaled, and rotated so that features in frame att₀ are aligned with matching features in the frame at t₀+Δt.

After image registration methods are applied, any mismatch betweenframes from a camera 104 indicates temporary distortion caused byturbulence or darkening due to clouds. Clouds can be distinguished fromturbulence as clouds decrease the overall brightness in an image,whereas distortion caused by turbulence rearranges the brightness, butdoes not generally decrease the overall brightness in the frame. In oneembodiment, the computer 108 eliminates frames containing clouds. Inanother embodiment, the computer 108 uses only those features in theframe where the moon 122 or sun 124 is not blocked by clouds.

Referring now to FIG. 3B, in one embodiment, a camera 104 (FIG. 3A)observes a turbule 302 encroach on the edge of the sun 124 at time t₀.Referring now to FIG. 3C, at a later time, t₁=t₀+Δt, the camera 104images the turbule 302 begin to exit the other edge of the sun 124.Referring now to FIG. 3A, the interval Δt depends on three variables:the angular width, α, of the sun 124; the distance to the turbule 302 orheight, h_(t); and the velocity, v, of the turbule 302. The distance tothe sun 124, or h_(s), is known, and α is also known. Given Δt, theratio of h_(t) and v can be computed using trigonometry. In oneembodiment, the values for h_(t) and v are estimated, for example basedupon expected values such as the expected velocity or expected height ofthe jet stream.

In another embodiment, two cameras 104 may be utilized to determine thedistance h_(t) to the turbule 302, which allows determining the value ofthe velocity, v, of the turbule 302. Referring now to FIG. 4A, leftcamera 104 a is separated from right camera 104 b by distance d, forexample by mounting the left camera 104 a and right camera 104 b,collectively cameras 104, on opposite ends of the vehicle 102. Note thatalthough two cameras 104 are described as an exemplary embodiment, it isalso possible to perform the operation using additional cameras 104, oreven a single camera 104 capable of imaging a feature from two or morevantage points, for example using lenses, mirrors, or fiber optics.

Continuing to refer to FIG. 4A, and now referring to FIG. 4B, forpurposes of illustrating an aspect of the invention, a simplifiedembodiment of the system is shown as follows: left camera 104 a andright camera 104 b are shown in a line that is approximately horizontaland the sun 124 is in a vertical orientation perpendicular to the linebetween the cameras 104. Turbule 302 is shown moving parallel to theline between the cameras 104, in a direction from left to right. Asturbule 302 crosses in front of the sun 124, the left camera 104 a willdetect distortion caused by the turbule 302 at time t₀ before the rightcamera 104 b detects the distortion at time t₂=t₀+Δt, where Δt is equalto distance between the cameras 104, d, divided by the velocity of theturbule, v. (All vectors in the following equations are denoted inbold.) Because t₂, t₀, and d can be measured, v is computed as follows:v=d/(t ₂ −t ₀).  Equation (2)Once the turbule transits the feature at time t₁=t₀+αh_(t)/v for leftcamera 104 a, or time t₃=t₂+αh_(t)/v, then h_(t) can be computed byeitherh _(t)=(t ₁ −t ₀)v/α  Equation (3)orh _(t)=(t ₃ −t ₂)v/α  Equation (4)and therefore both the height h_(t) or distance to the turbule 302, andthe velocity vector, v, of the turbule 302 can be computed. The computer108 uses the distance to the turbule 302 and the angle to the turbule302 to determine the altitude of the turbule 302 relative to the earth110. Although this example assumes the sun 124 is directly above thecameras 104, it will be apparent to those skilled in the art that thesun 124 or other celestial objects 128 may be viewed at any angle fromvertical to nearly horizontal, and at any azimuth relative to the vectord connecting the two cameras 104, and that suitable trigonometryformulas may be used to compute the correct height, h_(t), and velocityvector, v, of the turbule 302.

Referring now to FIGS. 5A and 5B, an alternative mathematical approachis to determine the offset angle θ of the turbule 302 from the center ofthe sun 124 by both cameras 104. Left camera 104 a images an offset ofθ_(l) and right camera 104 b images an offset of θ_(r). The angulardifference between turbule 302 measured positions by each camera 104 isΔθ=θ_(l)−θ_(r), and h_(t) can be computed ash _(t) ≅d/Δθ  Equation (5)where all angles are in radians and are assumed to be smaller than 0.1radian. A turbule's 302 measured angular speed w relative to the cameras104 is computed by measuring the time Δt for turbule 302 to transit theangular width a of the sun 124. The turbule 302 velocity vector v iscomputed asv=ω/h _(t).  Equation (6)In practice, turbules 302 may be irregularly shaped, there may bemultiple turbules 302, and each turbule 302 may appear at a differentaltitude with a different wind speed and direction. The followingembodiments correlate image features to resolve individual turbules 302within a sequence of images taken by a single camera 104 and betweenimages taken by two or more cameras 104.

In Equation (6), the symbol ω refers to the measured angular velocity ofa turbule about the camera's location. That measurement treats the sunand the moon as unmoving background images with known angular widths α,so the angular velocity ω is computed as angular width α divided by thetime it takes for individual turbules to cross from one side of the sun(or moon) to the other.

When observing turbules in front of distant celestial bodies, one mayassume the angular velocity of the background object is zero relative tothe Earth's surface. However, to be more precise, the movement ofcelestial objects may be considered. For example, distant celestialbodies like the Pleiades move across the sky at the Earth's sideralrotation rate of one rotation (i.e., 2π radians) per 23.93447 hours,multiplied by the cosine of the object's celestial latitude. The sunalso moves across the sky due to the Earth's rotation, but with a smallcorrection (about one part in 365.24) due to the Earth's motion aboutthe sun. Further, the Earth's velocity changes from aphelion toperihelion, and with its orbital position relative to the moon, so thiscorrection varies slightly throughout the year. Various embodiments mayuse appropriate levels of detail in calculating the sun's angularvelocity.

The moon moves across the sky due to the Earth's rotation, but with asubstantial correction (about one part in 29.53) due to the moon'srevolution about the Earth. The moon's velocity changes from apogee toperigee, and its velocity relative to the Earth is confounded by otherinfluences like the sun's gravity, so this correction varies slightlythroughout the month and throughout the year. Various embodiments mayuse appropriate levels of detail in calculating the moon's angularvelocity.

Besides these actual motions that shift celestial objects across thesky, there is an apparent motion that becomes significant when celestialobjects are near the horizon. This motion is due to refractive bendingof light by the Earth's atmosphere. Dense air at low altitudes has ahigher index of refraction than thin air at high altitude. Light from acelestial object curves downward as it traverses the atmosphere. Thismakes objects near the horizon appear higher than they actually are. Theapparent path of a celestial object across the sky bends upward as theobject approaches the horizon.

Accordingly, in an embodiment, the camera 104 and image processor 108(FIG. 1) measure the angular velocity ω of the turbule 112 relative tothe Earth's surface 110, rather than relative to the sun, moon, planets,planets and their moons, or an asterism or constellation such as thePleiades. To do this, the image processor 108 still visually measuresthe apparent angular velocity of the turbule 112 relative to thecelestial background object 128 as previously described, but the imageprocessor then corrects this measurement by adding the angular velocityof the celestial background object, which it computes using informationabout celestial mechanics and atmospheric refraction. This correctiongives the “true” angular velocity ω of the turbule relative to a fixedposition on the Earth's surface.

Correlation of Images from a Camera

Referring now to FIGS. 6A and 6B, a first turbule 602 moves in a firstdirection at velocity v_(a), shown in FIG. 6B as generally traveling inthe direction of the x-axis, and a second turbule 604 moves in a seconddirection at velocity v_(b), shown in FIG. 6B as traveling more or lessin the direction of the y-axis. To distinguish the data associated withthe first turbule 602 from data associated with the second turbule 602,a mathematical correlation operation is performed to the data.

The correlation coefficient for two data sets, x_(i) and y_(i), eachhaving N elements, is defined asr=s _(xy) /s _(x) s _(y),  Equation (7)where s_(x) and s_(y) are the standard deviations of x_(i) and y_(i) andwhere s_(xy) is the covariance of x and y, defined ass _(xy)=(Σx _(i) y _(i)−1/NΣx _(i) Σy _(i))/(N−1)  Equation (8)where all sums are over the range I=1 . . . N.

For a pair of images x and y, where each image in an m_(x)n array ofpixels indexed by{(j,k):j=a . . . m,k=1 . . . n},  Equation (9)let N=m_(x)n and the summation index I=j+m(k−1). Then the correlationcoefficient of two images is defined asr=s _(xy) /s _(x) s _(y)  Equation (10)wheres _(xy)=(ΣΣx _(j,k) y _(j,k)−1/NΣΣx _(j,k) Σσy _(i,k))/(N−1)  Equation(11)and all double sums are over the range j=1 . . . m, k=1 . . . n.

The sequences of difference images from a single camera are correlatedto reveal the magnitude and angular velocity of turbulence at variousaltitudes. Continuing to refer to FIGS. 6A and 6B, and now referring nowto FIGS. 7A, 7B and 7C, first turbule 602 is at height h_(ta) and secondturbule 604 is at height h_(tb). Both the first turbule 602 and thesecond turbule 604 are moving across the visible disc of the sun 124 atthe same time, but in two different directions x, y, and at twodifferent velocities, v_(a), v_(b) respectively. The images in FIGS. 7A,7B, and 7C illustrate the turbules 602, 604 at four different times, t₁,t₂, t₃, t₄.

Referring now to FIGS. 8A, 8B and 8C, in an embodiment, the turbulenceand winds aloft measurement system 100 computes a sequence of differenceimages 802, 804, and 806, at various temporal and angular offsets. Thefirst difference image 802 is the difference between the image framethat captured first turbule 602 and second turbule 604 at time t₁, andthe image frame that captured first turbule 602 and second turbule 604at time t₂. Similarly, second difference image 804 is the differencebetween the images when turbules 602, 604 are at times t₂ and t₃, andthird difference image 806 is the difference image between times t₃ andt₄. As is understood in the art, an angular offset in the scenecorresponds to a pixel offset in the digital image. The angle isproportional to the number of pixels by which the image is offset,multiplied by the spatial width of a pixel, divided by the focal lengthof the lens. The temporal offset is the difference between the timeswhen the difference images were captured. An angular offset θ combinedwith a temporal offset Δt corresponds to an angular velocity ofω=θ/Δt.  Equation (12)When the temporal and angular offsets match the angular velocity ofturbules 602, 604 at a particular altitude h_(ta), h_(tb), there is apeak in the correlation coefficient, r(ω_(θ), ω_(φ)),

Referring now to FIGS. 9A and 9B, the correlation contour plotsillustrate the correlation r²(ω_(θ), ω_(φ)) 900 of the difference images802, 804, and 806 for angular velocity vectors ω_(θ) 906, and ω_(φ) 908.The correlation contour plots have two peaks 902, 904. The peaks 902,904 represent the angular velocities of the turbules 602, 604 with onepeak corresponding to ω_(a) 902 and one peak corresponding to ω_(b) 904.To measure the linear velocities v_(a), v_(b) of the turbules 602, 604requires knowledge of the altitudes h_(ta) and h_(tb).

In the previously discussed embodiment, methods are presented to derivev, the velocity of a turbule 112 (FIG. 1) relative to the camera 104,simultaneously with h, the height of a turbule relative to the camera.The velocity of the camera 104 was assumed to be zero relative to theEarth's surface.

In another embodiment (FIG. 1), the cameras 104 a and 104 b may bemounted on a moving platform 102 such as an ocean-going vessel. Theplatform 102 may have a nonzero mean velocity v_(platform), and theaction of wind and waves (in the case of an ocean-going vessel) maycause the platform to pitch, roll, yaw, heave, sway, and surge so thateach camera 104 a, 104 b may have a time-varying velocity v_(camera).This affects the apparent angular velocity ω of a turbule relative tothe camera, especially if v_(camera) is relatively large compared to theturbule velocity v.

With this other embodiment, the system 100 may include an imageprocessor 108 configured to continuously estimate v_(camera), from datareceived from the position and orientation system 106, that may includea GPS receiver and/or accelerometers mounted near the camera 104 on theplatform 102. This embodiment may use this measured camera velocityv_(camera) to correct its estimate of turbule velocity v and height h.Referring again to FIG. 4A and FIG. 4B, left camera 104 a and rightcamera 104 b are shown in a line that is approximately horizontal andthe sun 124 is in a vertical orientation perpendicular to the linebetween the cameras 104. However, in a case in which both cameras 104 a,104 b are moving with velocity v_(camera) to the right (not shown),turbule 302 may move parallel to the line between the cameras 104 a, 104b in a direction from left to right. As turbule 302 crosses in front ofthe sun 124, the left camera 104 a may detect distortion caused by theturbule 302 at a time t₀ before the right camera 104 b detects thedistortion at time t₂=t₀+Δt, where Δt is now equal to distance betweenthe cameras 104 a, 104 b, d, divided by the difference between thevelocity of the turbule, v, and of the cameras v_(camera). Because t₂,t₀, and d can be measured, v is computed as follows:V=d/(t ₂ −t ₀)+v _(camera)  Equation (12)Once the turbule transits the feature at time t1=t0+αht/(v−v_(camera))for left camera 104 a, or time t₃=t₂+αh_(t)(v−v_(camera)), then h_(t)can be computed by eitherh _(t)=(t ₁ −t ₀)(v−v _(camera))/α  Equation (13)orh _(t)=(t ₃ −t ₂)(v−v _(camera))/α  Equation (14)and there both the height h_(t) or distance to the turbule 302, and thevelocity vector v of the turbule 302 can be computed. The computer 108uses the distance to the turbule 302 and the angle to the turbule 302 todetermine the altitude of the turbule 302 relative to the Earth 110.Although this example assumes the sun 124 is directly above the cameras104, it will be apparent to those skilled in the art that the sun 124 orother celestial objects 128 may be viewed at any angle from vertical tonearly horizontal, and at any azimuth relative to the vector dconnecting the two cameras 104 a, 104 b, and that suitable trigonometryformulas may be used to compute the correct height, ht, and velocityvector v, of the turbule 302.

The camera 104 on a moving platform 102 also may have a time-varyingangular velocity due to the platform's rotation (pitch, roll, and yaw).To visually measure the angular velocity of an object relative to theEarth's surface 110, the angular velocity of the camera would have to besubtracted from the angular velocity of the object. However, with thisembodiment, the angular velocity of each turbule 112 is measured withrespect to a celestial object 128 whose angular velocity is known, so nocorrection for the camera's angular velocity is needed.

Correlation of Images from Cameras

To compute the altitudes h_(ta) and h_(tb) and the linear velocitiesv_(a), v_(b) of the turbules 602, 604, the positions of the turbules602, 604 are triangulated using two or more cameras 104. Referring nowto FIGS. 10A and 10B, a turbule 1002 moves at angular speed ω across thesun 124. FIG. 10A illustrates the imaging of the turbule 1002 by a firstcamera 104A at times t₁, t₂, t₃, and t₄ as the turbule 1002 transits thesun 124. FIG. 10B illustrates the imaging of the same turbule 1002 bythe second camera 104A at times t₃, t₄, t₅, and t₆.

Referring now to FIG. 11, the turbule 1002 is visible to both cameras104 during times t3 and t4. To measure the angular offset Δθ, or spatialshift of the position of the turbule 1002, the difference image from oneof the cameras 104 is shifted along the direction of the other camera104, and the correlation coefficient r(Δθ) is computed at variousangular distances Δθ. The distance Δθ at which a correlation peak occursreveals the altitude h_(t) of the turbule 1002 relative to the camera104, as given by h_(t)≅d/Δθ (Equation (5)).

Referring now to FIGS. 12A and 12B, the turbule 1002 is not visible toboth cameras 104 at the same times, t₁-t₇. The turbule is visible tocamera 104 a during times t₁, t₂, t₃, and t₄; and the turbule is visibleto camera 104 b during times t₅, t₆, and t₇. There is therefore noangular offset Δθ that allows a correlation peak in r(Δθ) to match theturbule 1002 images from both cameras 104. Instead, the differenceimages from one camera 104 are correlated with the difference imagestaken by another camera 104 at a different time, either earlier orlater, and using angular offsets with non-zero Δφ.

Referring now to FIG. 13, a correlation peak in r(Δt, Δθ, Δφ) occurswhen Δt=4 frames, Δθ˜0.4α, and Δφ˜0.6 α, where α is the angular width ofthe sun 124. Correlating over a three-dimensional range of offsets Δt,Δθ, and Δφ is computationally more expensive than correlating over theone-dimensional range, Δθ. In one embodiment, the computer 108 firstattempts to correlate over the one-dimensional range, Δθ, and thenattempts to correlate over the three dimensional range of offsets Δt,Δθ, and Δφ if computational bandwidth is available. In anotherembodiment, the computer 108 is optimized to correlate over the threedimensional range of offsets Δt, Δθ, and Δφ.

Multiple Camera Configurations

In various embodiments, the turbulence and winds aloft measurementsystem 100 may comprise one, two, or multiple cameras 104. The abilityfor the turbulence and winds aloft measurement system 100 to accuratelyresolve the altitude of turbules 112, 302, 602, 604, and 1002 may dependin part upon the distance between the cameras 104. For example, cameras104 that are close together generally see the same turbules 112, 302,602, 604, and 1002, making computations easier, but cameras 104 that arefurther apart may resolve angular distances to a finer granularity. Alsoturbules 112, 302, 602, 604, and 1002 at lower altitudes will havegreater angular displacements frame-to-frame for a given linear velocitybecause they are closer to the cameras 104, making computations possibleeven for relatively closely placed cameras 104, that is, cameras 104that may be separated by a relatively small d. Turbules 112, 302, 602,604, and 1002 that are higher in the atmosphere will have relativelylower angular displacement frame-to-frame, and thus will require greaterdistances between cameras 104 in order to resolve accurately.

In an embodiment, a first pair of cameras 104 are separate by a distanceof approximately 10 meters, while a third camera 104 is separated fromthe pair of cameras 104 by approximately 100 meters. The first pair ofcameras 104 provide good characterization of turbules 112, 302, 602,604, and 1002 at lower altitudes, while the third camera 104 facilitatescharacterizing turbules 112, 302, 602, 604, and 1002 at high altitudes.

In an embodiment, the cameras 104 are mounted on an ocean-going vehicle102, for example a ship or vessel. For example, the first pair ofcameras 104 might be mounted near the bow of a vessel on either side ofthe deck, while the third camera might be mounted further back on thevessel closer to the stern.

In an embodiment, the cameras 104 are located roughly at the corners ofan equilateral triangle on the surface of the earth 110. Thisconfiguration ensures that turbules 112, 302, 602, 604, and 1002traveling in any direction within a selected altitude range will besimultaneously visible to at least two of the cameras 104 during part ofthe turbules 112, 302, 602, 604, and 1002 transit across the sun 124.This configuration also allows using one-dimensional angular offsets forcorrelation between each pair of cameras 104, which is computationallyless costly than the three-dimensional offsets needed to achieve similarcoverage with, for example, two cameras 104 a, 104 b.

Single Camera Configuration

A central problem encountered by the system 100 is that turbulence ischaracterized by two unknowns: height and velocity. Slow-movingturbulence at low altitude has the same apparent angular velocity asfast-moving turbulence at high altitude, so a single set of observationscannot resolve the actual height and velocity of a turbule 112. Inpreviously described embodiments, a solution is to take measurements attwo or more spaced-apart locations, such as by triangulatingmeasurements from two cameras 104 a, 104 b (FIG. 1) spaced a modestdistance apart.

As previously described, an embodiment may use cameras 104 a, 104 bmounted on a moving (or unsteady) platform 102. When the moving platform102 has non-uniform velocity, such as the motion of a ship or a buoyaffected by waves at sea, in an embodiment, the system 100 may usemeasurements from a single camera 104 (i.e., camera 104 a alone orcamera 104 b alone) moving with two or more velocity vectors.

If the camera 104 moves with the same velocity vector as the turbule112, then the apparent angular velocity of the turbule is zero. If thecamera 104 moves at the same speed as the turbule 112, but in theopposite direction, then the apparent angular velocity of the turbule istwice as great as if the camera were stationary. Given two suchmeasurements, namely, one in which the turbule 112 has zero angularvelocity and one in which the camera 104 moves at the same speed but inthe opposite direction, speed of the turbule can be determined.

Mathematically, calculating the speed of the turbule 112 can begeneralized to cases where the measured angular velocities do not happento include zero. As shown in FIG. 14, at a low altitude, the camera 104(FIG. 1) moves with velocity v_(camera) relative to the Earth's surface112 (represented by the lower grid 110′). At a higher altitude(represented by the upper grid 114′), turbules 112 move with a differentvelocity v_(turbule). The altitude difference between the camera 104 andthe turbules 112 is h. The line of sight from the camera to a turbulepassing in front of the sun or moon is vector r.

In this embodiment, the camera 104 measures apparent motion of theturbules 112 over a brief interval, during which the camera velocityv_(camera) is roughly constant. (This uniform velocity may be assumedbecause the interval is brief, or the processor 108 may use measurementsof velocity or acceleration to select an interval during which thevelocity is roughly constant.) The measured angular velocity of theturbules is given by:ω={tilde over (r)}×(v _(turbule) −v _(camera))/r.  Equation (15)That is, the angular velocity is the cross product of {tilde over (r)}(the unit vector in the r direction) and the turbules' velocity relativeto the camera 104, divided by the distance r from the camera to theturbules 112.

After one such measurement, three values are known: ω (angular velocityof the turbules), {tilde over (r)} (the direction from the camera 104 tothe turbules 112), and camera velocity v_(camera). Velocity v_(turbule)and distance r remain unknown. To compute their values, the inventiontakes two angular velocity measurements, ω₁ and ω₂. Each measurementcomprises at least two image frames, using the method previouslydescribed. The two measurements occur while the camera is moving at twosubstantially different velocity vectors, v_(cam1) and v_(cam2). Themeasurements are close enough in time that r and v_(turbule) can beassumed to change very little, namely, the first measurement may occuras a ship-mounted camera 104 rolls to the right and the secondmeasurement may occur at a subsequent time (i.e., after a time interval)as the same camera rolls to the left. The angular velocity measurementsare related to the camera velocities as shown here:ω₁ ={tilde over (r)}×(v _(turbule) −v _(cam1))/r  Equation (16)ω₂ ={tilde over (r)}×(v _(turbule) −v _(cam2))/r.  Equation (16)

Equation (16) and Equation (17) are each multiplied by r and rearrangedusing the distributive property of cross products over addition:ω₁ r={tilde over (r)}×v _(turbule) −{tilde over (r)}×v _(cam1)  Equation(18)ω₂ r={tilde over (r)}×v _(turbule) −{tilde over (r)}×v _(cam2)  Equation(19)

Equation (19) is subtracted from Equation (18) to give:(ω₁−ω₂)r={tilde over (r)}×(v _(cam2) −v _(cam1))  Equation (20)The result is rearranged to solve for the distance r:r={tilde over (r)}×(v _(cam2) −v _(cam1))·(ω₁−ω₂)/|(ω₁−ω₂)|²  Equation(21)where “·” indicates a dot product and |(ω₁−ω₂)| is the magnitude ofvector (ω₁−ω₂).

A less rigorous, but computationally more expedient, embodiment may usethe following formula instead:r={tilde over (r)}×(v _(cam2) −v _(cam1))/|(ω₁−ω₂)|  Equation (22)Given the value of r and the direction of {tilde over (r)}, thisembodiment may use well-known trigonometry to compute height h, e.g.,h=r {tilde over (r)}·k, where k is the unit vector in the z direction.

To compute v_(turbule), Equation (16) is rearranged:rω ₁ ={tilde over (r)}×v _(turbule) −{tilde over (r)}×v_(cam1)  Equation (23)and the term containing v_(turbule) is isolated:{tilde over (r)}×v _(turbule) ={tilde over (r)}×v _(cam1) −rω₁.  Equation (24)The cross product on the left is expanded to identify its vectorcomponents:{tilde over (r)}×v _(turbule) =i({tilde over (r)} _(y) vz−{tilde over(r)} _(z) vy)+j({tilde over (r)} _(z) vx−{tilde over (r)} _(x)vz)+k({tilde over (r)} _(x) vy−{tilde over (r)} _(y) vx).  Equation (25)where i, j, and k are unit vectors in the x, y, and z directions. It isassumed that, on average, a group of turbules 112 moves horizontallywith the wind at altitude h, even though individual turbules may move upor down within a body of air. Given this assumption, the verticalcomponent of v_(turbule), v_(z), goes to zero, as do all termscontaining it in Equation (25):{tilde over (r)}×v _(turbule) =i(−{tilde over (r)} _(z) v _(y))+j({tildeover (r)}zv _(x))+k({tilde over (r)} _(x) v _(y) −{tilde over (r)} _(y)v _(x)).  Equation (26)

Recalling Equation (24), each component of Equation (26) must match thecorresponding component of the right side of Equation (24). Inparticular, the i-components Equation (27)) and the j-componentsEquation (28)):−{tilde over (r)}_(z) v _(y) =i·({tilde over (r)}×v _(cam1) −rω₁)  Equation (27){tilde over (r)} _(z) v _(x) =j·({tilde over (r)}×v _(cam1) −rω₁).  Equation (28)Since the processor 108 already has measured or calculated every valuein Equation (27) except v_(x) and every value in Equation (28) exceptv_(y), Those two values now can be calculated. They jointly determinev_(turbule):v _(turbule) =iv _(x) +jv _(y).  Equation (29)

With the single-camera embodiment, the processor 116 throughcommunications system 116 may report h, v_(x), and v_(y), namely,altitude, speed, and direction of winds aloft. This embodiment also mayuse previously described methods to estimate and report the magnitude ofturbulence at each altitude, but now does so with a single camera.

Communications

In an embodiment, the turbulence and winds aloft measurement system 100further comprises a communications link 116 to transfer estimates ofturbulence, turbules 112, and winds 114 aloft. In embodiments, thecommunications link 116 may receive and transmit estimates. Inembodiments, the communications links 116 may permit transfers ofestimates with aircraft 118, a weather service provider 130, a nationalweather agency, an airline operations center, a military aircraftcommand center, and/or a solar or lunar information service forobtaining up-to-date images of the sun 124 and moon 122.

In an embodiment, the turbulence and winds aloft measurement system 100may communicate information to the pilot, navigator or other operator ofthe vehicle 102. In an embodiment, the turbulence and winds aloftmeasurement system 100 may send the estimates to a weather forecastingcenter or weather service provider 130. In an embodiment, the turbulenceand winds aloft measurement system 100 may share the information withnearby aircraft 118 or systems on the ground. In an embodiment, theturbulence and winds aloft measurement system 100 may share raw orinterpreted data with nearby vehicle 102 to develop a better indicationof local turbulence, turbules 112, and winds aloft 114. In anembodiment, the data may be is shared via military communications links,for example Link-16.

The embodiments of the invention shown in the drawings and describedabove are exemplary of numerous embodiments that may be made within thescope of the appended claims. It is contemplated that numerous otherconfigurations of the turbulence and winds aloft measurement system 100may be created taking advantage of the disclosed approach. It is theapplicant's intention that the scope of the patent issuing herefrom willbe limited only by the scope of the appended claims.

What is claimed is:
 1. A turbulence and winds aloft detection system,comprising: an image capturing device for capturing a plurality ofimages of a visual feature of a selected celestial object; and an imageprocessor configured to compare the plurality of images of the visualfeature to detect a transit of a turbule of turbulent air between theimage capturing device and the selected celestial object; compensate forone or more of apparent visual motion of celestial objects due to aplanet's translation and rotation, the moon's revolution about theplanet, and the atmosphere's refractive displacement of celestialobjects; and compute a measurement of at least one of a velocity of theturbule and a height of the turbule relative to the planet.
 2. Theturbulence and winds aloft detection system of claim 1, furthercomprising a lens having a focal length adapted to focus an image ontosaid image capturing device such that a combination of said lens andsaid image capturing device is adapted to resolve a distortion of saidvisual feature caused by turbulent air.
 3. The turbulence and windsaloft detection system of claim 1, wherein the image capturing device isa charge coupled device (CCD) camera.
 4. The turbulence and winds aloftdetection system of claim 1, wherein the celestial object is selectedfrom the group consisting of the moon, the sun, a plurality of stars,and a planet; and wherein the visual feature is selected from the groupconsisting of an edge of a solar disc, a sunspot, a solar granule, anedge of a lunar disc, a lunar crater, a lunar mountain range, a lunarshadow, a relative position of each of the plurality of stars, and aposition of moons about the planet.
 5. The turbulence and winds aloftdetection system of claim 1, further comprising a filter disposedbetween the image capturing device and the celestial object, wherein thefilter is selected from the group consisting of a helium I filter, ahydrogen alpha filter, a solar filter, a neutral density filter, apolarizing filter, an narrowband filter, a wideband filter, and anoptically colored filter.
 6. The turbulence and winds aloft detectionsystem of claim 1, wherein the image capturing device is mounted on amobile platform and the image processor is adapted to estimate avelocity of the image capturing device relative to the planet; and touse the velocity of the image capturing device to correct an estimate ofone or more of the velocity of the turbule relative to the planet and aheight of the turbule above the planet.
 7. The turbulence and windsaloft detection system of claim 6 wherein the mobile platform isselected from the group consisting of a marine vessel, a land vehicle,an aircraft, and a spacecraft.
 8. The turbulence and winds aloftdetection system of claim 6, further comprising at least one of a globalpositioning satellite (GPS) receiver and one or more accelerometers toprovide the image processor with data on the velocity of the imagecapturing device.
 9. A turbulence and winds aloft detection system,comprising: an image capturing device for capturing a plurality ofimages of a visual feature of a selected celestial object; a device forsensing motion of the image capturing device relative to the Earth; andan image processor configured to compare the plurality of images of thevisual feature to detect a transit of a turbule of turbulent air betweenthe image capturing device and the selected celestial object; receive asignal from the motion sensing device to continuously estimate avelocity of the image capturing device relative to the Earth; andcompute a measurement of at least one of a velocity of the turbulerelative to the Earth and a height of the turbule relative to the Earth.10. The turbulence and winds aloft detection system of claim 9 whereinthe motion sensing device includes at least one of a global positioningsatellite (GPS) receiver and at least one accelerometer, the at leastone accelerometer being associated with the image capturing device forsensing motion of the image capturing device.
 11. The turbulence andwinds aloft detection system of claim 9 wherein the height of theturbule relative to the Earth is computed by comparing a first measuredangular velocity of the turbule relative to the image capturing devicemoving at a first velocity at a first measurement time with a secondangular velocity of the turbule relative to the image capturing devicemoving at a second velocity at a subsequent second measurement time. 12.The turbulence and winds aloft detection system of claim 9 wherein thevelocity of the turbule relative to the Earth is computed at apredetermined height of the turbule by comparing a measured angularvelocity of the turbule relative to a velocity of the image capturingdevice.
 13. A method of detecting turbulence and winds aloft,comprising: capturing a plurality of images of a visual feature of aselected celestial object; comparing the plurality of images to detectthe transit of a turbule of turbulent air in front of the selectedcelestial object; and processing the plurality of images to compensatefor one or more of apparent visual motion of celestial objects due to aplanet's translation and rotation, the moon's revolution about theplanet, and the atmosphere's refractive displacement of celestialobjects; and computing a measurement of at least one of an angularvelocity of the turbule and the height of the turbule.
 14. The method ofclaim 13, wherein the capturing step includes capturing a plurality ofimages of a visual feature of a selected celestial object selected fromthe group consisting of the moon, the sun, a grouping of stars, and aplanet; and wherein the visual feature is selected from the groupconsisting of an edge of a solar disc, a sunspot, a solar granule, anedge of a lunar disc, a lunar crater, a lunar shadow, a relativeposition of each of the grouping of stars, and a position of moons aboutthe planet.
 15. The method of claim 13, wherein the capturing isperformed by an image capturing device mounted on a mobile platform andthe processing includes continuously estimating a velocity of the imagecapturing device relative to the planet; and using the velocity of theimage capturing device to correct an estimate of one or more of thevelocity of the turbule relative to the planet and a height of theturbule above the planet.
 16. The method of claim 15, wherein the mobileplatform is selected from the group consisting of a marine vessel, aland vehicle, an aircraft, and a spacecraft.
 17. The method of claim 15,wherein the processing includes receiving data from at least one of aglobal positioning satellite (GPS) receiver and one or moreaccelerometers on the velocity of the image capturing device.
 18. Amethod of detecting turbulence and winds aloft, comprising: capturing aplurality of images of a visual feature of a selected celestial objectwith an image capturing device; sensing motion of the image capturingdevice relative to the Earth; processing the plurality of images of thevisual feature to detect a transit of a turbule of turbulent air betweenthe image capturing device and the selected celestial object; usingsensed motion of the image capturing device to continuously estimate avelocity of the image capturing device relative to the Earth; andcomputing a measurement of at least one of a velocity of the turbulerelative to the Earth and a height of the turbule relative to the Earth.19. The method of claim 18 wherein the height of the turbule relative tothe Earth is computed by comparing a first measured angular velocity ofthe turbule relative to the image capturing device moving at a firstvelocity at a first measurement time with a second angular velocity ofthe turbule relative to the image capturing device moving at a secondvelocity at a subsequent second measurement time.
 20. The method ofclaim 18 wherein the velocity of the turbule relative to the Earth at apredetermined height of the turbule is computed by comparing a measuredangular velocity of the turbule relative to the image capturing device.21. The method of claim 18 wherein the velocity measurement is correctedfor the velocity of the image capturing device.